OBJECT-BASED CHANGE DETECTION USING A NEURAL NETWORK

摘要

A method is described for determining a change in an object or class of objects in image data, wherein the method comprises: receiving a first image data set of a geographical region associated with a first time instance and receiving a second image data set of the geographical region associated with a second time instance; determining a first object probability map on the basis of the first image data set and a second object probability map on the basis of the second image data set, a pixel in the first and second object probability maps having a pixel value, the pixel value representing a probability that the pixel is associated with the object or class of objects; providing the first object probability map and the second object probability map to an input of a neural network, preferably a recurrent neural network, the neural network being trained to determine a probability of a change in the object or class of objects, based on the pixel values in the first object probability map and in the second object probability map; receiving an output probability map from an output of the neural network, a pixel in the output probability map having a pixel value, the pixel value representing a probability of a change in the object or class of objects; and, determining a change in the object or class of objects in the geographical region, based on the output probability map.